Making good decisions is an important requirement for leaders in all types of institutions, such as business, industry, and government. Such decisions must often be made regarding choices between candidates. For example, business leaders must often select a product to develop and manufacture, from among candidates consisting of a large number of potential products. Similarly, purchasing managers often decide which product to purchase for use in a company, choosing from candidates consisting of large numbers of products offered for sale by vendors. In the personnel area, employees are hired and promoted by selecting from candidates consisting of many applicants. In the government area, it is often necessary to select a policy from candidates consisting of a number of possible alternative policies.
In some situations, leaders make decisions based on subjective intuitive factors. Good leaders are often those having good instincts permitting wise decisions. In some cases however, decision making must be more objective. This is especially true in situations where the decision maker does not have absolute power, but is required to justify his decision and convince others that his decision is correct.
Objective decision making is often based on numeric data used to describe various factors, or dimensions, of candidates. Such data is often presented in numeric tables. Recently, "spreadsheet" computer programs have become popular as a means for organizing numeric data and generating numeric results presented in tables, based on calculations performed on input data. Spreadsheets permit convenient change of input data to produce almost immediate output. This in turn permits convenient consideration of "what if" questions to observe the influence of various factors upon the final numeric objective output data.
In addition to tables, objective decision making often involves the use of various types of graphs to present numeric data. "Pie" charts and bar graphs, often enhanced with color, have improved the presentation of objective data used in decision making.
Despite recent advances in the ability to manipulate numeric data and display such data in graphical form, it remains difficult to convey and absorb descriptive data, especially where such data is present in multiple dimensions. Such multiple dimensions often require multiple numeric tables and multiple charts. Even those with skill and experience in working with numeric data may have difficulty analyzing and interpreting such multiple charts and tables. Thus, presently known methods of data display do not provide a convenient way to display data having multiple dimensions, in a manner that can be readily absorbed by a decision maker to permit effective selection of choices between various candidates. Accordingly, it is desired to provide a method for displaying data in a manner in which various dimensions of the data can be readily understood, absorbed, and interpreted.